American Journal of Mathematical and Computer Modelling

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Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria

Received: 13 February 2018    Accepted: 08 April 2018    Published: 10 May 2018
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Abstract

This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.

DOI 10.11648/j.ajmcm.20180301.14
Published in American Journal of Mathematical and Computer Modelling (Volume 3, Issue 1, March 2018)
Page(s) 27-37
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Environmental Health, Diseases, Forecast, Model, Fuzzy Logic

References
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[16] Idowu, P., Cornford, D., and Bastin, L. (2008). Health Informatics Deployment in Nigeria. Journal of Health Informatics in Developing Countries, 2(1):20-21.
[17] Idowu P. A. (2012) A Spatial Data Model for HIV/AIDS Surveillance and Monitoring in Nigeria. International Journal of E-Health and Medical Communications. 3(2): 66-84.
[18] Idowu Peter Adebayo (2017) Predictive Model for the Classification of Hypertension Risk Using Decision Trees Algorithm, American Journal of Mathematical and Computer Modelling. 2(2):48-59.
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Author Information
  • Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria

  • Engineering Materials Development Institute, Federal Ministry of Science & Technology, Akure, Nigeria

  • Department of Computer Science, Ogun State Institute of Technology, Igbesa, Ogun State, Nigeria

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  • APA Style

    Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. (2018). Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. American Journal of Mathematical and Computer Modelling, 3(1), 27-37. https://doi.org/10.11648/j.ajmcm.20180301.14

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    ACS Style

    Peter Adebayo Idowu; Olufemi Komolafe; Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am. J. Math. Comput. Model. 2018, 3(1), 27-37. doi: 10.11648/j.ajmcm.20180301.14

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    AMA Style

    Peter Adebayo Idowu, Olufemi Komolafe, Racheal Adefunke Oladejo. Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria. Am J Math Comput Model. 2018;3(1):27-37. doi: 10.11648/j.ajmcm.20180301.14

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  • @article{10.11648/j.ajmcm.20180301.14,
      author = {Peter Adebayo Idowu and Olufemi Komolafe and Racheal Adefunke Oladejo},
      title = {Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria},
      journal = {American Journal of Mathematical and Computer Modelling},
      volume = {3},
      number = {1},
      pages = {27-37},
      doi = {10.11648/j.ajmcm.20180301.14},
      url = {https://doi.org/10.11648/j.ajmcm.20180301.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajmcm.20180301.14},
      abstract = {This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - Fuzzy Logic Model to Forecast Environmental Related Health Diseases in Nigeria
    AU  - Peter Adebayo Idowu
    AU  - Olufemi Komolafe
    AU  - Racheal Adefunke Oladejo
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    DO  - 10.11648/j.ajmcm.20180301.14
    T2  - American Journal of Mathematical and Computer Modelling
    JF  - American Journal of Mathematical and Computer Modelling
    JO  - American Journal of Mathematical and Computer Modelling
    SP  - 27
    EP  - 37
    PB  - Science Publishing Group
    SN  - 2578-8280
    UR  - https://doi.org/10.11648/j.ajmcm.20180301.14
    AB  - This paper identified the risk factors for environmental health related diseases and formulated a fuzzy logic based predictive model based on the identified variables. Related literatures were reviewed so as to understand the body of knowledge surrounding environmental health related diseases and their corresponding risk factors, interviews with community health officers were conducted in order to validate the identified variables. Fuzzy logic was used to formulate the predictive model using Matlab Fuzzy logic tool box. Data was collected from five different states in Nigeria. The result showed that there are cases of environmental related diseases in the areas where there is no potable water and in locations that lack good toilet facilities. In the areas where there is no toilet facility or where bucket and bush are used as toilet, there are always cases of cholera. In these areas during the rainy season cholera outbreaks are common occurrences. All these points to fact that, if there is a good environmental health tracking system with predictive features, then environmental health officers would be able to easily monitor, manage and track any area which may be prone to any of these environmental health diseases.
    VL  - 3
    IS  - 1
    ER  - 

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